Hybridized Heuristic Heterogeneous Mathematical modeling for sustainable International comparison of the economic efficiency in nuclear energy
Sustainable Energy Technologies and Assessments, ISSN: 2213-1388, Vol: 50, Page: 101578
2022
- 2Citations
- 17Captures
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Article Description
To achieve sustainable solutions to the current problems in energy, it is required to analyze sustainable development factors, environmental conditions, long-term plans, and actions that are considered as crucial. Energy is currently prevalent, and nuclear power resembles to provide one aspect of an efficient and sustainable solution. In this paper, Hybridized Heuristic Heterogeneous Mathematical Model (HHHMM) has been proposed for the sustainable International comparison of the economic efficiency of Nuclear energy. The proposed mathematical model is derived that nuclear energy is economically feasible to produce a progressive share of future electricity supply to achieve increasing electricity in the economy. Furthermore, the assessment is performed for a Nuclear energy integration system included a Small Modular Reactor (SMR) where a portion of the heat produces is used for the production of hydrogen via high-temperature steam electrolysis (HTSE).In addition, the economic risk is calculated by excessive energy costs and varying energy consumption, economic reactor indices and CO2 emissions constraints. Finally, the Economic loss probability distribution functions, feasibility and Sustainable Efficiency Factor (SEF) for nuclear energy strategies has been analyzed in the experimental results. Based on the analysis, there is a long-term relationship among the parameters and the effect on energy efficiency from energy sources is positive and energy from renewable sources is more advantageous in terms of energy efficiency with nuclear energy.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2213138821005920; http://dx.doi.org/10.1016/j.seta.2021.101578; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85120155059&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2213138821005920; https://dx.doi.org/10.1016/j.seta.2021.101578
Elsevier BV
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